1. Field of the Invention
The present invention relates to the field of measuring apparatuses, and particularly to a measuring apparatus allowing for measuring the three-dimensional characteristics of an object by using range data acquisition and analysis as well as a method for such measuring.
2. Description of the Related Art
Two-dimensional (2D) smart cameras combine 2D image acquiring, processing, and analyzing into a single device wherein all of the functionality is highly configurable. Several processing steps can be applied in any order. The output from one step can be used to configure subsequent steps. Intermediate values can be stored and used at a later stage. These values can then control aspects such as the data flow, the output format, and parameters in the processing and analyzing. This highly configurable analysis is called dynamic analysis. This is opposed to static analysis, where the same analysis step sequence is performed on each image regardless of intermediate results.
A typical inspection task is to first locate an object shape which has been taught to the system. Once located, features such as areas, edges, or corners of the object can be determined. The properties of the features are then analyzed and the result is typically some form of classification result (e.g. accepted/rejected), a measurement (e.g. object area), or a combination of such values.
The configuration is performed by attaching a PC or other control hardware to the device. The configuration is typically made using some form of graphical user interface where acquired images are shown as an aid in the configuration. After configuration, the device can run as a stand-alone product without any PC or other control hardware connected.
However, it is not possible to acquire and process range data, also known as three-dimensional (3D) data, in these types of units.
Range imaging is used to obtain a set of range values, and compared to ordinary 2D imaging the pixel values of a range image do not represent the light intensity, but rather the distance between the camera and the measured object. There are a number of well-known techniques for measuring range data. These include laser triangulation, structured light imaging, time-of-flight measurements and stereo imaging.
A number of commercially available devices produce range data as output. These devices are typically adapted to a processing unit, such as a PC, for processing, analysis and/or storage of the range data. These devices output a stream of range data values. The values can be organized in different ways. A one-dimensional set of range values measured along a line across the object is referred to as a profile. A number of subsequent profiles form a range image. Just as an ordinary two-dimensional image, the range image consists of a two-dimensional set of pixels. The difference is that the pixel values of the range image depict shape rather than light intensity.
A number of commercially available range imaging products process the data before producing an output. The output is then the result of the processing. All of these products process the range values on a profile-per-profile basis. The processing is limited to produce a single measurement such as the profile area or the position of an edge. The analysis is static in the sense discussed above. An example of such a range imaging product is the sheet-of-light sensor DMH from SICK AG, Germany.
The level of configuration available in existing range imaging devices and the profile-per-profile analysis are not sufficient for many inspection tasks. The user typically needs to develop custom software functionality outside of the device that processes the range data in order to obtain useful properties of the scanned object. Just as in a 2D smart camera, a typical inspection task consists of locating one or more objects in an image and then performing different measurements on the found objects. The results should be reported according to some user-configurable protocol to other devices. Such dynamic analysis is not available in existing range imaging devices.
One prior art approach is shown in U.S. Pat. No. 6,542,235, which discloses a three-dimensional inspection system for inspecting circular parts. The system comprises one to four cameras which generate profile signals of a part to be inspected. The profile signals are forwarded to a computer which analyzes the signals and generates a 2D height image of the inspected part. The height image of the inspected part is analyzed by comparing it to known good part data in order to determine whether the inspected part is satisfactory or unacceptably defective. The system is user-configurable to some degree, e.g. operator-selected distance between parts to be inspected, operator-selected part number for inspection, operator-started inspection process, etc. In addition, the system may be calibrated from typical “pixels” to real world units, such as square inches or square millimeters per area and inches or millimeters for linear measures.
However, the system according to the above-described document is not highly user-configurable in the sense of a 2D smart camera as discussed above. Further, the above-described system is used for inspecting circular parts, i.e. symmetrical parts (objects). The use of calibrated height images (from pixel units to real world units) as input to a 2D image analysis system, when the object has an asymmetrical shape, will result in that presented objects vary in size and shape depending on the position relative to the camera. These distortions are generally not handled properly by the calibration functionality found in existing analysis systems.
There is therefore a need for an improved imaging apparatus and method for measuring the three-dimensional characteristics of an object, which combines the flexible configuration abilities of a 2D smart camera with the data acquisition of a range camera into a single unit, and which overcomes the distortion problem stated above.